An Application of Nonlinear Mixed-Effects Modeling to Pharmacokinetic Data Exhibiting Nonlinear and Time-Dependent Behavior

2003 ◽  
Vol 92 (1) ◽  
pp. 27-34 ◽  
Author(s):  
L. Iavarone ◽  
R. Gomeni
Keyword(s):  
Mixed Effects ◽  
Time Dependent ◽  
Pharmacokinetic Data ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Modeling ◽  
Mixed Effects Modeling ◽  
Dependent Behavior

scholarly journals Effect ofSLCO1B1Polymorphisms on Rifabutin Pharmacokinetics in African HIV-Infected Patients with Tuberculosis

2015 ◽  
Vol 60 (1) ◽  
pp. 617-620 ◽  
Author(s):  
Stefanie Hennig ◽  
Suhashni Naiker ◽  
Tarylee Reddy ◽  
Deirdre Egan ◽  
Tracy Kellerman ◽  
...  
Keyword(s):  
Drug Exposure ◽  
Mixed Effects ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Modeling ◽  
Tuberculosis Patients ◽  
Host Genetics ◽  
Mixed Effects Modeling ◽  
Complex Interactions ◽  
Multiple Doses ◽  
Heterozygous Carriers

ABSTRACTRifabutin, used to treat HIV-infected tuberculosis, shows highly variable drug exposure, complicating dosing. Effects ofSLCO1B1polymorphisms on rifabutin pharmacokinetics were investigated in 35 African HIV-infected tuberculosis patients after multiple doses. Nonlinear mixed-effects modeling found that influential covariates for the pharmacokinetics were weight, sex, and a 30% increased bioavailability among heterozygous carriers ofSLCO1B1rs1104581 (previously associated with low rifampin concentrations). Larger studies are needed to understand the complex interactions of host genetics in HIV-infected tuberculosis patients. (This study has been registered at ClinicalTrials.gov under registration no. NCT00640887.)

scholarly journals Parameter Estimation of Population Pharmacokinetic Models with Stochastic Differential Equations: Implementation of an Estimation Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Fang-Rong Yan ◽  
Ping Zhang ◽  
Jun-Lin Liu ◽  
Yu-Xi Tao ◽  
Xiao Lin ◽  
...  
Keyword(s):  
Differential Equations ◽  
Likelihood Function ◽  
Estimation Algorithm ◽  
Mixed Effects ◽  
Population Pharmacokinetic ◽  
Pharmacokinetic Data ◽  
Pharmacokinetic Models ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Models ◽  
Mixed Effects Modeling

Population pharmacokinetic (PPK) models play a pivotal role in quantitative pharmacology study, which are classically analyzed by nonlinear mixed-effects models based on ordinary differential equations. This paper describes the implementation of SDEs in population pharmacokinetic models, where parameters are estimated by a novel approximation of likelihood function. This approximation is constructed by combining the MCMC method used in nonlinear mixed-effects modeling with the extended Kalman filter used in SDE models. The analysis and simulation results show that the performance of the approximation of likelihood function for mixed-effects SDEs model and analysis of population pharmacokinetic data is reliable. The results suggest that the proposed method is feasible for the analysis of population pharmacokinetic data.

scholarly journals Nonlinear mixed effects modeling of growth in Japanese quail

2013 ◽  
Vol 92 (7) ◽  
pp. 1942-1948 ◽  
Author(s):  
Emre Karaman ◽  
Dogan Narinc ◽  
Mehmet Ziya Firat ◽  
Tulin Aksoy
Keyword(s):  
Japanese Quail ◽  
Mixed Effects ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Modeling ◽  
Mixed Effects Modeling

scholarly journals Pharmacokinetic Similarity of Biologics: Analysis Using Nonlinear Mixed-Effects Modeling

2011 ◽  
Vol 91 (2) ◽  
pp. 234-242 ◽  
Author(s):  
A Dubois ◽  
S Gsteiger ◽  
S Balser ◽  
E Pigeolet ◽  
J L Steimer ◽  
...  
Keyword(s):  
Mixed Effects ◽  
Nonlinear Mixed Effects ◽  
Nonlinear Mixed Effects Modeling ◽  
Mixed Effects Modeling
Sign in / Sign up

Export Citation Format

Share Document